The present invention relates to a system and a method for evaluating noise and sound, and more particularly, relates to a system and a method for evaluating noise and sound based on an autocorrelation function (hereinafter called xe2x80x9cACFxe2x80x9d) and an interaural crosscorrelation function (hereinafter referred to as xe2x80x9cIACFxe2x80x9d).
The present invention also relates to a system and a method for measuring and subjectively evaluating environmental noise such as automobile noise and aircraft noise, and more particularly, relates to a system and a method for measuring and subjectively evaluating noise on the basis of a binaural system.
Environmental noise such as atrafic noise and aircraft noise has been discussed previously with a sound pressure level and its frequency characteristic measured by using a noise level meter in monaural. However, it has been recognized that only the physical factors measured by the noise level meter in monaural mentioned above could not express sufficiently and appropriately the subjective response of the human beings. In the field of concert hall acoustics, it has been revealed that physical data of the hall in a binaural system has relevance to psychological (subjective) evaluation, whereas, in the field of the research of environmental noise, only physical data such as spectrum information in the monaural system has been dealt with.
Up to now, in the music field, in order to tune instruments as well as to evaluate tone, at first sound spectrum has been analyzed, and then ceptsrum analyzing has been effected.
For many years, the environmental noise has been evaluated in terms of the statistical sound pressure level (SPL), represented as Lx or Leq and its power spectrum measured by a monaural sound level meter. The SPL and power spectrum alone, however, do not provide a description that matches subjective evaluations of the environmental noise.
Also, it is difficult to express appropriately psychological responses to sound by the conventional method for evaluating timble and for tuning tone.
It is an object of the present invention to provide a system, a method and a storage media for identifying a category of a noise source by using physical factors derived from an autocorrelation function ACF which always changes in the time domain as well as from an interaural crosscorrelation function IACF of a binaural signal on the basis of the human auditory-brain system.
It is another object of the present invention to provide a system, a method and a storage media for subjectively evaluating more precisely timbre, scale, loudness, pitch, tone color, perception of duration, subjective diffuseness, apparent source width for the sound field by using physical factors derived from ACF and IACF which are ever changing in the time domain based on the human auditory brain function system.
In order to attain the above mentioned objects, a method for evaluating noise and sound according to the present invention comprises the steps of:
capturing the sound and converting the captured sound into an acoustic signal;
calculating an autocorrelation function ACF by processing the acoustic signal with the aid of a computing means;
calculating at least one autocorrelation function factor (ACF factor) from the calculated ACF with the aid of the computing means; and
evaluating the sound in accordance with said at least one ACF factor and a preestablished database with the aid of the computing means, said database storing at least one of the following data; tone data associating tones with ACF factors, prosodic data associating prosodic elements with ACF factors and subjective evaluation data associating subjective evaluation values with ACF factors.
According to the invention, the sound can objectively be evaluated by reading data from said preestablished database (storing data that associate various kinds of information of various musical instruments which have been evaluated to generate good sounds (scale values of, for instance, tone color, prosodic element, timbre and subjective diffuseness, scale values of apparent source width ASW and subjective evaluation values) with ACF factors and IACF factors); and by comparing the readout data with the ACF factor extracted from the acoustic signal of the target sound to derive a difference therebetween, numerical value of the difference or a degree of the difference. When the sound evaluating method according to the present invention is applied to manufacturing of musical instruments, adjustment of tone color or timbre and tuning of tonal scale, it is objectively and appropriately possible to attain an instrument which would be evaluated subjectively to have good tone color. Also, an instrument can objectively and appropriately be tuned. In other words, according to the invention, instruments which have been manufactured in accordance with craftsman""s intuition could be manufactured in accordance with the objective data.
In an embodiment of the sound evaluating method according to the invention, said step of calculating at least one ACF factor comprises calculating at least one of the following ACF factors: energy "PHgr"(0) represented at the origin of the delay (i.e. delay time is zero); an effective duration xcfx84e; a delay time of a maximum peak xcfx841; an amplitude of the maximum peak of the normalized ACF xcfx861; and information of respective peaks within the delay time (from zero to xcfx841) xcfx84nxe2x80x2, xcfx86nxe2x80x2 (n=1, 2, 3, . . . , N (N is an integer less than approximately 10)).
According to this embodiment, a musical instrument having a subjective evaluation denoting better tone color can be more objectively and more appropriately manufactured based on the various ACF factors mentioned above and the instrument is also more objectively and more appropriately tuned.
Another embodiment of the sound evaluating method according to the invention further comprises the steps of:
calculating a pitch frequency based on the delay time xcfx841 of the ACF; and
comparing the calculated pitch frequency with data of a predetermined tonal scale database to derive a difference therebetween to perform tuning.
According to this embodiment, under favor of the phenomenon such that an inverse number of the xcfx841 calculated from the sound signal correlates the pitch frequency, the musical scale of the intended instrument can appropriately be tuned. In this connection, it is possible that the predetermined tonal scale database may be superseded by the said predetermined database.
Another embodiment of the sound evaluating method according to the invention further comprises the steps of:
capturing the sound in a binaural manner and converting the captured sound into an acoustic binaural signal;
calculating an interaural crosscorrelation function IACF between left and right channels from the acoustic binaural signal with the aid of computing means;
calculating at least one interaural crosscorrelation function factors from the calculated interaural crosscorrelation function IACF with the aid of the computing means; and
evaluating the sound or evaluating subjectively the sound based on the IACF factors and/or the ACF factors and the said preestablished database with the aid of the computing means.
According this embodiment, the sound evaluation and the subjective sound evaluation can objectively and appropriately be accomplished by comparing evaluation values of spatial subjective sensations such as a subjective diffuseness extracted from the IACF with data stored read out of the database to derive differences between them.
The principal conception of the present invention may be realized not only as the method mentioned above but also as a system.
For instance, a sound evaluation system according to the invention comprises:
sound capturing means for capturing a sound and converting the captured sound into an acoustic signal;
ACF calculating means for calculating an autocorrelation function ACF from the acoustic signal;
ACF factor calculating means for calculating autocorrelation function factors from the calculated autocorrelation function ACF; and
evaluating means for evaluating the sound based on the ACF factors and a predetermined database storing at least one of the following data; tone data associating tones with ACF factors, prosodic data associating prosodic elements with ACF factors and subjective evaluation data associating subjective evaluation values with ACF factors.
In an embodiment of the sound evaluating system according to the invention, said ACF factor calculating means comprises calculating means for calculating at least one of the following ACF factors: energy "PHgr"(0) represented at the origin of a delay (i.e. delay time is zero); an effective duration xcfx84c; a delay time of a maximum peak xcfx841; an amplitude of a maximum peak of a normalized ACF xcfx861; and information of respective peaks within the delay times (from zero to xcfx841) xcfx84nxe2x80x2, xcfx86nxe2x80x2 (n=1, 2, 3, . . . , N (N is an integer less than approximately 10)).
In still another embodiment of the sound evaluation system according to the invention, the system further comprises:
pitch frequency calculating means for calculating a pitch frequency from xcfx841 of the ACF; and
tuning means for comparing the calculated pitch frequency with data read out of a predetermined tonal scale database to represent a difference between them.
In still another embodiment of the sound evaluating system according to the invention, the system further comprises:
capturing means for capturing the sound in a binaural manner and converting the captured sound into an acoustic binaural signal;
IACF calculating means for calculating an interaural crosscorrelation function IACF between right and left channels from the acoustic binaural signal;
IACF factor calculating means for calculating an interaural crosscorrelation function factors from the calculated interaural crosscorrelation function IACF; and
evaluating means for evaluating the sound or evaluating subjectively the sound based on the IACF factors and/or the ACF factors and the said preestablished database.
According to further aspect of the present invention, a method for identifying a kind of a noise source comprises the steps of:
capturing and recording a sound signal from an environmental noise source to be identified using sound recording means;
calculating an autocorrelation function ACF from the recorded sound signal by Fourier transform with the aid of computing means;
calculating autocorrelation function factors from the calculated autocorrelation function ACF with the aid of the computing means; and
identifying a kind of the noise source based on the calculated autocorrelation function factors with the aid of the computing means.
In a preferable embodiment of the sound source identifying method according to the invention, said autocorrelation function factor calculating step comprises a step of calculating the following autocorrelation function factors: energy "PHgr"(0) represented at the origin of delay (i.e. delay time is zero); effective duration xcfx84e; delay time of a first peak xcfx841; and amplitude of a first peak of a normalized ACF xcfx861 from said autocorrelation function ACF; and said identifying a kind of a noise source comprises the steps of:
calculating logarithms of the energy "PHgr"(0) represented at the origin of a delay (i.e. delay time is zero), an effective duration xcfx84c, a delay time of a first peak xcfx841, and an amplitude of a first peak of a normalized ACF xcfx861 (the xcfx84nxe2x80x2 and xcfx86nxe2x80x2 may contingently be added) and deriving absolute values of differences (i.e. distances) between these logarithms and corresponding logarithms in templates previously made in accordance with the respective autocorrelation function factors of various noise sources;
deriving weighting coefficients for the respective autocorrelation function factors by dividing standard deviations (S2) of arithmetic means of the respective autocorrelation function factors by an arithmetic mean (S1) of standard deviations of all categories of the autocorrelation function factors to derive quotients and by calculating square roots of the quotients;
multiplying the respective distances with corresponding weighting coefficients for the respective autocorrelation function factors to find a total distance; and
comparing the thus obtained total distance with the distances in the stored templates to select one of the distances, which is proximate to the total distance.
According to another aspect of the invention, a method for evaluating subjectively a noise source comprises the steps of:
recording acoustic signals of an environmental noise in a binaural manner using sound recording means;
calculating an autocorrelation function and an interaural crosscorrelation function between right and left ear channels from the acoustic signals with aid of computing means;
calculating autocorrelation function factors from the ACF and/or calculating interaural crosscorrelation function factors from the IACF with the aid of the computing means; and
subjectively evaluating a noise source based on the autocorrelation function factors and/or the interaural crosscorrelation function factors with the aid of the computing means.
The present invention has been mainly described as methods, however it is understood that the present invention may be realized as systems corresponding to the methods, programs embodying the methods as well as a storage media storing the programs.
Description of many subjective attributes such as preference and diffuseness, as well as primary sensations (loudness, pitch, and timbre) can be based on a model of response of the human auditory-brain system to sound fields, and the predictions of the model have been found to be consistent with experimental results. The loudness of band-limited noise, for example, has recently been shown to be affected by the effective duration of the autocorrelation function (ACF), xcfx84c, as well as by the SPL. When a fundamental frequency of complex tones is below about 1200 Hz, the pitch and its strength are influenced by a delay time of the first peak xcfx841 and an amplitude of a first peak of the normalized ACF xcfx861, respectively. In particular, the ACF factors obtained at (xcfx84c)min are good indicators of differences in the subjective evaluation of the noise source and the noise field.
The model comprises autocorrelators for the signals at two auditory pathways and an interaural crosscorrelator between these signals, and it takes into account of the specialization of the cerebral hemisphere in humans. The ACF and interaural crosscorrelation function (IACF) of sound signals arriving at both ears are calculated. Orthogonal factors "PHgr"(0), xcfx840, xcfx841, and xcfx861 are extracted from the ACF. The IACF factors LL (sound pressure level), IACC (peak magnitude), xcfx84IACC (delay time of the peck magnitude), and WIACC (width of the peak magnitude) are extracted from the IACF.